Video-based analysis is one of the most important tools of animal behavior and animal welfare scientists. While automatic analysis systems exist for many species, this problem has not yet been adequately addressed for one of the most studied species in animal science—dogs. In this paper we describe a system developed for analyzing sleeping patterns of kenneled dogs, which may serve as indicator of their welfare. The system combines convolutional neural networks with classical data processing methods, and works with very low quality video from cameras installed in dogs shelters.
|Title of host publication||Artificial Neural Networks and Machine Learning – ICANN 2019|
|Subtitle of host publication||Image Processing - 28th International Conference on Artificial Neural Networks, 2019, Proceedings|
|Editors||Igor V. Tetko, Pavel Karpov, Fabian Theis, Vera Kurková|
|Number of pages||12|
|State||Published - 2019|
|Event||28th International Conference on Artificial Neural Networks, ICANN 2019 - Munich, Germany|
Duration: 17 Sep 2019 → 19 Sep 2019
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||28th International Conference on Artificial Neural Networks, ICANN 2019|
|Period||17/09/19 → 19/09/19|
Bibliographical noteFunding Information:
This work has been supported by the NVIDIA GPU grant program.
© Springer Nature Switzerland AG 2019.
- Animal science
- Animal welfare
- Computer vision
- Convolutional neural networks
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science (all)